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Mechanical M2
RoboCAD designs
[FINAL REPORT – ENGI 8926 ]
1
Executive Summary
This report concludes the work done this term, Winter 2013, for the group M2, RoboCAD Designs. The
introduction briefly outlines the peripherals of each section. From this is the introduction of the initial
phases of the design process, namely, the discussion of important topics necessary for the functioning of
an actively-controlled biped robot. This includes design constraints, objectives, research, and design
considerations. Furthermore, several concepts are provided in this report from which the final design is
derived from. Also included is the work performed on the modelling process; from the CAD designs to
the construction of the robot, and to the simulations.
Following the introduction and planning stages of the production of the robot, the analysis of its
functionality was investigated. Research was performed on the stability and support phases of a walking
robot, as well as the walking swing phase. In conjunction with this, in more detail, is research regarding
the foot of the robot, as well as the comparison between the human and our robot’s gait. The analysis
concludes with calculations of various dynamic aspects; namely the position, velocities, accelerations,
and forces of the leg and joints of the machine.
Finally, concluding remarks of the project are presented, as well as some future suggestions for work.
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Table of Contents
1 Introduction .......................................................................................................................................... 5
2 Problem Statement ............................................................................................................................... 6
3 Design Constraints ................................................................................................................................ 6
4 Design Objectives .................................................................................................................................. 7
4.1 Energy and Cost Efficiency ............................................................................................................ 8
4.2 Self-Balancing ................................................................................................................................ 9
4.3 Durability ....................................................................................................................................... 9
4.4 User Friendly Controls................................................................................................................... 9
5 Research .............................................................................................................................................. 10
5.1 Stability and Support ................................................................................................................... 10
5.2 Walking Phase ............................................................................................................................. 12
6 Concept Generation ............................................................................................................................ 14
6.1 Concept 1 .................................................................................................................................... 14
6.2 Concept 2 .................................................................................................................................... 15
7 Design Considerations......................................................................................................................... 16
7.1 The Foot ...................................................................................................................................... 17
7.2 Gait and Gait Selection ............................................................................................................... 19
8 Final Concept ...................................................................................................................................... 20
8.1 Leg Design ................................................................................................................................... 21
8.2 Frame .......................................................................................................................................... 23
8.3 Steering ....................................................................................................................................... 23
8.4 Control System ............................................................................................................................ 24
9 Modelling ............................................................................................................................................ 27
9.1 Developing References through capture of human leg locomotion .......................................... 28
9.2 Ground and Collision Simulation (Simulink) ............................................................................... 30
10 Analysis ........................................................................................................................................... 31
10.1 Foot Locus of Leg Linkages .......................................................................................................... 31
10.1.1 Vector Loops ....................................................................................................................... 34
10.1.2 Quality ................................................................................................................................. 37
10.2 Gait Selection .............................................................................................................................. 39
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10.3 Pin Forces .................................................................................................................................... 39
11 Conclusions ..................................................................................................................................... 40
12 Appendix A – Motion Analysis (Hand Calculations) ........................................................................ 42
13 Appendix B – Inverse Dynamics (Hand Calculations) ...................................................................... 46
14 Appendix C – Motion Analysis Code (MATLAB) .............................................................................. 49
15 Appendix D – C++ code ................................................................................................................... 55
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Figure 5-1: Example of Organization of Perception and Control of a Walker ............................................ 11
Figure 5-2 Human Gait Cycle....................................................................................................................... 12
Figure 5-3 Percentile Breakdown of Time Spent in Each Walking Phase ................................................... 14
Figure 6-1 Concept 1 ................................................................................................................................... 15
Figure 6-2 Concept 2 ................................................................................................................................... 16
Figure 7-1 Illustration of motion of foot with respect to crank rotation .................................................... 17
Figure 7-2 Theoretical Foot Locus (shown by bold black line) .................................................................... 18
Figure 8-1 Final Design Concept.................................................................................................................. 20
Figure 8-2 sideview of final concept with labeled links .............................................................................. 22
Figure 8-3 Progression of the frame ........................................................................................................... 23
Figure 8-4 Top view of steering mechanism capabilities ............................................................................ 24
Figure 8-5 Control logic for CARL ................................................................................................................ 25
Figure 8-6 Atmega644p & L293D chips showing pin connections .............................................................. 26
Figure 8-7 Controller board ........................................................................................................................ 27
Figure 9-1 SLR camera ................................................................................................................................. 29
Figure 9-2 positions of the hip, knee, and ankle joints during walking ...................................................... 29
Figure 9-3 Current ground model accounting for position and velocity .................................................... 31
Figure 10-1 Theo Jansen Mechanism Linkages ........................................................................................... 32
Figure 10-2 MATLAB foot position .............................................................................................................. 37
Figure 10-3 Gait Diagram ............................................................................................................................ 39
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1 Introduction
A lot of research has been put forth into the development of humanoid robots. They are used as a
research tool in several areas such as in biomechanics, human cognition, and personal assistance. With
regards to biomechanics, a humanoid robot may be used to have a better understanding of the human
structure. There have also been advancements in human sensory and its relation to perceptual and
motor skills, which are used to develop computational models. A humanoid robot may be able to
perform human tasks as well, such as work in hazardous environments, assembly lines, and help the
physically disadvantaged.
There are two possible bipedal walkers; a passive-dynamic walker and an actively-controlled walker. A
passive-dynamic walker is able to function without the use of any motors, and is generally capable of
manoeuvring slopes in a manner similar to that of humans. An actively-controlled walker, however, rely
on actuators and motors to produce and control joint torques for locomotion. In general, biped robots
have better mobility than conventional wheeled robots; however, they are also unstable as they are
more susceptible to tipping, which are, in part, due to the alternating leg during motion. . In order for
bipedal robots to be able to walk stably in various environments, such as on rough terrain, on inclines
and declines, or in environments that contain obstacles, it is necessary for the robot to adapt to the
ground conditions with a foot motion and maintain its stability with a torso motion in a manner similar
to humans. Research has been conducted to study human locomotion by observing people as they walk,
measuring joint angles, ground reaction forces and the complete walking cycle parameters.
For our term project, we are focusing on the capabilities of an actively-controlled bipedal system which
will be able to walk, turn, and traverse various terrains. We will research existing information on
bipedalism, with the focus held on the human gait which includes the balancing and control of robotic
locomotion.
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Since the propse of the project is to design a remote controlled robot, we should be wary of the
complications of having too many input signals. Thus, an important goal is to simplify the design and as a
result, we developed a concept that will only rely on two motors. Of course, the robot will be remote
controlled, but it will also be capable of using a rechargeable battery.
Along the vein of developing a simple machine, we’ve determined that the robot be energy and cost
efficient, possess user friendly controls, be durable and self-balancing. All of this, keeping in mind the
ease and safety of construction, as well as any waste material created in the process.
At the end of this project, we have developed a prototype of our actively-controlled biped robot.
2 Problem Statement
The purpose of this project is to design a remote controlled bipedal robot. The proposed design should
only make use of two motors to turn and propel it, and should be fully capable of maintaining its
balance during motion as it traverses a level horizontal plane. Although not part of the main scope of
the project, the robot’s performance on sloped terrains will also be assessed in order to determine the
versatility of the final design. The final design will incorporate aspects of an idealized biomechanical
system; the musculoskeletal system of a bipedal animal will be lumped into a pair of limbs and feet.
3 Design Constraints
Design Constraints
The project general restrictions are as follows;
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I. The system must only use two motors to produce motion
II. The system will not use any sensors to guide its motion or adjust limb positions
III. The system should be designed to be an untethered remote controlled robot
IV. The system design should incorporate a power supply that is rechargeable
V. The power supply should be detachable from the main body of the robot
VI. The design should be safe to operate
VII. The system should not require any assembly before use, the end product should be one whole,
fully assembled device
VIII. The following performance restrictions have been set in order to guide design;
IX. The system should be capable of turning left and right
X. The system should be able to walk along any prescribed course over a level horizontal plane
As the project advances into in-depth design phase and prototype creation phase, more constraints will
be introduced. These constraints will mostly relate to the geometric features of the prototype being
developed.
4 Design Objectives
The primary aim of this project is to develop a mechanism that allows for the movement of a bipedal
vehicle over a variety of terrains. To facilitate the process of creating this vehicle, the following design
objectives have been set. The robot should be:
I. Energy and Cost Efficient
II. Self-balancing
III. Durable
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IV. User-friendly
4.1 Energy and Cost Efficiency
Under the specific constraints outlined in the previous section, it is important to make use of and be
efficient with the available resources, specifically with the cost and power requirements.
Movement is provided solely through the input of two motors. These, along with a receiver, will be
powered with a battery on the system itself. The addition of a battery increases the net weight of the
system dramatically, as it is the heaviest component, and will increase the load required by the motor.
In conjunction with this aspect is the walking dynamics of the system. Take into consideration a
multispeed bicycle. Each gear setting dictates the number of rotations a pedal must undergo to
complete one rotation of the rear wheel. In a case where the bicycle is moving uphill, the easiest
method for a rider to traverse the incline is to increase the number of pedal rotations per wheel
rotation. In a similar manner, with an increased load, due to the torques, friction, and inertia of the
parts, the power requirements of a motor increase as well.
In addition to the motor requirements is the gait of the machine, which includes variables such as the
step distance and weight distribution.
Ideally, the design should incorporate lightweight, strong parts that are able to withstand typical forces
encountered during the human gait while easing the load on the motor (and ultimately reduce the
power costs). Associated with those qualities, however, are the costs of the materials as well as the time
required to produce and modify the parts. For instance, it would not be ideal to have parts that need to
be machined, and if so, could be done easily and readily. The design should incorporate mostly
inexpensive materials, and the overall cost of producing the scaled prototype should not exceed
$450.00.
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4.2 Self-Balancing
To ensure that the machine does not tip, it will be designed to ensure that its center of mass always falls
inside its base of support. This will ensure that the vehicle is not prone to falling over regardless of what
phase of walking the vehicle is currently in. This is especially important because the center of mass is
constantly shifting over each leg, much like the human body.
4.3 Durability
Any joints, hinges or linkages must be designed to withstand stresses of irregular terrain. The vehicle will
primarily be traversing level terrain, however, even level terrain will have irregularities on the surface
and as such the design must incorporate a sufficiently high design safety factor in order to ensure that
deformation or failure of any part does not occur.
4.4 User Friendly Controls
The vehicle is required to be remotely controlled. It is important that the controls are simple and require
little training to learn. The system response to the controls should be quick, as close to a real-time
response as possible to ensure that the vehicle can be effectively steered to avoid unpredicted obstacles
and make impulsive turns. Essentially, the vehicle should be able to change course at the user’s whim.
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5 Research
5.1 Stability and Support
The main principle of stability and control explains that as long as the center of pressure remains within
the polygon of the stance foot, the foot will remain firmly planted on the ground. Satisfaction of this
principle ensures that dynamical degrees of freedom remain fully actuated at all times, and thus control
design can be performed systematically using standard tools in robotics. However, the motions which
are achievable are highly conservative, inefficient and look unnatural. Most robots forgo full actuation
and allow gravity and the natural dynamics to play a large part in the generation of motion. A possible
organizational structure for the perception and control of a dynamic walker on rough terrain is depicted
in Figure [5-1] wherein the main components are:
I. Terrain Perception: fusion of sensors such as vision, radar and laser, perhaps combined with
predefined maps, generating a model of the terrain ahead.
II. Motion Planning: uses the terrain map, current robot state, and a model of the robot’s dynamics
to plan a finite-horizon feasible sequence of footstep locations and joint trajectories. Slow time-
scale: motion plan might be updated once per footstep.
III. Motion Control: feedback control to stabilize the planned motion in the face of inaccurate
modeling, disturbances, time delays, etc.
IV. Robot State Sensing: optical encoders, accelerometers, gyros and foot pressure sensing.
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Figure 5-1: Example of Organization of Perception and Control of a Walker
Commonly, bipedal robots include the addition of hip joint actuation, upper body, flat feet and linear
spring-based compliance on ankle joints. These aim for adaptive bipedal locomotion with optimization
based controller. The model consists of an upper body (point mass added stick) that rotates around the
hip joint, a point mass representing the pelvis, two legs with knee joints, and ankle joints and two mass
added flat feet.
The mass of each leg is simplified as point masses added on the Centre of Mass of the shank and the
thigh respectively. A kinematic coupling is often used to keep the body midway between the two legs. In
addition, most models involve added compliance in ankle joints. Specifically, the ankle joints are
modeled as passive joints that are constrained by linear springs. Static balance walking is often achieved
along a horizontal plane although numerous terrain orientations can be derived. The definition of static
equilibrium is equivalent to the condition that the center of mass should be located within the polygon
of support. On this basis, the defined margin of static stability, at any instant, is the shortest distance
between the vertical projection of the biped’s center of gravity and the boundary of the support
polygon.
It is important to note that the proposed design will be remote controlled and therefore will not require
terrain perception. Typically, the control systems generate walking motions by modifying the nominal
walking pattern suitable to the terrain sensed ahead. However, adaptive gait control would not be
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possible without sensors and as such, the final design will rely on the physical characteristics of the
robot’s structural material to adjust for terrestrial irregularities.
5.2 Walking Phase
Double support occurs when both feet are on the ground and single support when only one limb is on
the ground. During single support phases whilst walking along a straight path, the projection of the
biped’s center of gravity must be between the two extremities of the stance foot. During double support
phases, the projection of the biped’s center of gravity must be between the tip of the forward foot and
the end of the rear foot. For a biped in single support on a flat floor, the velocity and acceleration of the
generalized coordinates of biped are zero, the projection of the inertia center and the contact pressure
center between the sole and the ground are merged. The gait cycle is the time between successive foot
contacts of the same limbs, thus one gait cycle begins when the reference foot contacts the ground and
ends with subsequent floor contact of the same foot, visually presented in figure [5-2].
Figure 5-2 Human Gait Cycle
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The human gait has a double support phase in which the body weight is supported by both legs. The
durations of stance phases are longer than swing phases throughout a neutral walk animation. The
stance to swing ratio is 3:2 on average. As the walking speed increases, the swing phase gets longer and
the stance phase gets shorter. In running the stance/swing ratio reverses and double support phases
disappear.
Double support occurs for two periods of 12% of the gait cycle in a normal walk. Double support occurs
between heel strike of the limb and toe off of the contra-lateral limb. In general, as walking speed
increases, double support time is reduced until it is eliminated and the gait changes to running. During
running the gait cycle for each leg is composed of a single support phase and a float or airborne phase.
Single limb support occurs for two periods of 38% of the gait cycle in a normal walk.
To summarize the stance phase of gait can be divided into three periods:
I. Contact period, when the heel strikes the ground going on to the foot flat period.
II. The mid-stance period of the stance phase when the foot is flat on the ground moving on to
heel lift.
III. The propulsive period of the stance phase when the heel is lifted off the ground and the toe off
position is taken.
The time percent analysis of walking is shown in Figure [5-3].
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Figure 5-3 Percentile Breakdown of Time Spent in Each Walking Phase
6 Concept Generation
6.1 Concept 1
For this concept, turning involves the use of solenoids and torsional springs to turn the robot. The design
of the leg motion has not been developed for this idea. To initiate a turn, either the left or right
solenoid on each foot will be engaged to disengage the gear (left solenoid to turn right, right solenoid to
turn left). The motor will continue to rotate and the leg coupled with the gear still engaged will continue
to take steps and the robot will pivot around the disengaged leg. The torsional spring (located in each of
the ankles) will tighten in the disengaged leg as the robot turns. This allows the foot to re-align to a
forward position when the robot finishes the turn, the disengaged leg re-engages, and takes its next
step.
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Forward motion will be the result of motor rotating the connected gear which will in turn rotate the two
connected gears and in doing so lift the leg and project it forward to take a step. The gears are aligned in
such a manner as to ensure that the legs are out of phase by 180⁰. Balance would be maintained by
using a gear with an unbalanced mass as the main driving gear. This would shift the weight from side to
side as the robot walks. This concept is shown in figure [6-1].
Figure 6-1 Concept 1
6.2 Concept 2
This concept employs a modified Theo – Jansen Mechanism as its leg linkage design as shown in figure
[6-2]. It utilizes two motors; one to rotate the shaft that couples legs 1 & 2 and the other to change the
angular orientation of the legs to facilitate a turn.
16
The turning mechanism employed in this concept is similar to that employed in car steering wheels. It
relies heavily on the Cardan universal joint to transfer the rotation of the primary shaft to the crank that
drives the legs whilst allowing the direction in which the legs are pointing in to be changed. The second
motor is used to adjust the direction of the legs by simply rotating in one direction or the other.
Balancing will be facilitated by sliding a mass back and forth to shift the center of mass and this
movement will be the result of the mass being attached to scotch yoke mechanism coupled to the main
shaft using a series of gears.
Figure 6-2 Concept 2
7 Design Considerations
A crank based walking mechanism refers to a mechanism with a linkage that has a point that moves
along a circular path. This circular movement results in a planar translation elsewhere in the linkage or
attached linkages. In the case of this project, the crank mechanism will be driven by one of two motors.
This section of the report will discuss aspects of the vehicle leg design
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7.1 The Foot
The foot is the part of the vehicle that comes into contact with the ground or surface. As the vehicle
walks, the foot moves in a cyclical path relative to the main body of the walker. This path is known as
the locus and consists of four parts; support, lift, return, and lower phases. Note that the lift, return, and
lower phases can be lumped into one phase, the transfer phase. During the support phase, the foot is in
contact with the ground providing support to the vehicle. During the lift phase, the foot is moving up
towards the maximum height of the locus. During the return phase, the foot has reached the maximum
height of the locus and is moving in the same direction of the vehicle. During the lower phase, the foot
lowers until it reaches the ground. A theoretical foot locus is shown in Figure [7-1] below;
Figure 7-1 Illustration of motion of foot with respect to crank rotation
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Figure 7-2 Theoretical Foot Locus (shown by bold black line)
These locus phases, as shown in figure [7-2] will be important in the leg design as they will dictate the
walking traits the vehicle exhibits. To meet the design objectives set for this project the following
conditions should be incorporated into the leg design;
I. The ratio of time spent in the support phase to the overall duration of the full locus
should be equal to or greater than 0.5. This maximizes the amount of time the foot
spends in contact with the ground and thus increases the stability of the vehicle
throughout the gait.
II. The lift phase of one leg should be paired with the lower phase of the other as this will
minimize the net forces of on the crank and increase energy efficiency
III. The length of the stride, the length of space traversed during the support phase, should
be long relative to the dimensions of the vehicle. This will ensure that the vehicle moves
further with each locomotive cycle and thus increases the systems energy efficiency.
IV. The step height should be sufficient enough to prevent the feet from dragging. This will
improve the vehicle stability as it would reduce the forces on the foot that could cause
19
the vehicle to tip whilst preventing the gait from being affected by the irregularities of
the terrain surface. Preventing dragging will also reduce energy losses in the system.
V. The loci of both legs should be identical
7.2 Gait and Gait Selection
A gait refers to positions of the legs of a multi-legged system during a full locomotive cycle. Gait
selection refers to a process of adjusting features of the crank-based mechanism in order to assign each
leg of the vehicle to a prescribed position during each point of the locomotive cycle. This is important as
the system energy efficiency can be maximized by adjusting the relative phase of each leg such that the
torque on the crank is minimized. The system stability can be maximized by sequencing the steps of
each leg to ensure that the gait is statically stable over most of the locomotive cycle. The following
aspects of the vehicle gait must be analyzed during the design and optimization phase;
I. Placing Event: This refers to the movement from the transfer phase to the support
phase
II. Lifting Event: The movement from support phase to the transfer phase
III. Duty Factor (βi): This is a ratio of the duration of support phase to the cycle time. This is
typically >0.5 for human walking gaits.
IV. Leg Phase: This is the fraction of the locomotive cycle by which leg 2’s placing event lags
behind leg 1’s placing event
For a bipedal vehicle, the gait selection is limited to wave gaits and equal phase gaits. A wave uses a
wave function to determine the leg phase as a function of the duty factor. It is commonly used by many
insects and animals. An equal phase gait is one in which the lifting and placing events are evenly
distributed throughout the locomotive cycle. This selection has the benefit of being energy efficient as it
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minimized the torque on the crank shaft. There are two categories of equal phase gaits; half cycle equal
phase gait and full cycle equal phase gait. Half cycle equal phase gaits are the result of equally
distributing the placing events of the feet on one side of the walker over a span of half of the locomotive
cycle. Full cycle equal phase gaits, on the other hand, are the result of equally distributing the placing
events of the feet on one side of the walker over a span of the full locomotive cycle.
8 Final Concept
Figure 8-1 Final Design Concept
It was important that the final concept meet all of the design requirements set in the research and
concept development phase. This concept employs a modified version of the Theo-Jensen mechanism as
its leg design.
21
This concept utilizes only two motors; one to turn the machine as introduced in section [6.2], and the
other motor to provide forward locomotion. The design is shown in figure [8-1].
The current design of CARL involved a process of creating a three-dimensional model in SolidWorks
based on the proportions needed to create the desired motion and gait according to Theo-Jensen’s
mechanism.
The turning mechanism employed in this concept is similar to that employed in car steering wheels. It
relies heavily on the Cardan universal joint to transfer the rotation of the primary shaft to the crank that
drives the legs whilst allowing the direction in which the legs are pointing in to be changed. The second
motor is used to adjust the direction of the legs by simply rotating in one direction or the other.
Balancing will be facilitated by sliding a mass back and forth to shift the center of mass and this
movement will be the result of the mass being attached to scotch yoke mechanism coupled to the main
shaft using a series of gears.
8.1 Leg Design
The design for CARL’s legs came from the design of Theo Jansen’s mechanism, called the Strandbeest.
Jansen’s mechanism is comprised of a collection of 11 linkages and is capable of moving on its own with
only natural forces acting upon it. Only the leg design was used for our purpose. Jansen came up with
his design with the intent of modeling an ideal walking gait, with the least amount of time of the “foot”
in the air. The shape made by the walking foot looks like a triangle with rounded corners and with the
longest, horizontal part being the base of the step.
As it takes a step, the foot moves through the top two, short sides quickly, while the other foot is on the
horizontal step. Jansen used a computer program to find the ideal ratio of linkages to get as close to the
ideal step as possible (rounded triangle). The ideal link ratios are as follows in table [8-1]:
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Link # Link #
A 38 G 36.7
B 41.5 H 65.7
C 39.3 I 49
D 40.1 J 50
E 55.8 K 61.9
F 39.4 L 7.8
M 15
Table 8-1
Figure 8-2 sideview of final concept with labeled links
For CARL’s leg dimensions, the ratios were divided by ten and given imperial units. The material chosen
for the linkages was acrylic plastic (Plexiglas). This will provide a strong material as well as ease the
speed of production with the use of a laser cutter.
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8.2 Frame
Initially, the only requirements set for the frame were the dimensions between the attachments for link
M and link BDE. The center of the frame was removed to save money by reducing the amount of the
material used in construction. As motors were selected and the steering design was refined, the framed
started to take a more practical shape. Material was added in some areas for motor support and
redundant material was removed for cost efficiency. Small holes were extruded through the side to
create attachment points for the controller board, or any other accessories.
When the size and arrangement of leg linkages were determined, the frame was designed according to
the dimensions of the selected motors, the controller boards, the steering design, and the layout of the
motors.
Figure 8-3 Progression of the frame
8.3 Steering
The steering was designed with the idea of car steering in mind. A motor coupled with a 14 ½°, 24 pitch
rack and 24 pitch spur gear are located in the front of the frame. As the motor is engaged, the rack
translates the rack and pushes the front part of the legs (Link BDE) to one side (see figure [8-4]). A
universal joint connects the drive shaft to Link M, which ensures that the link is able to rotate even
when not aligned perpendicular to the frame.
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Figure 8-4 Top view of steering mechanism capabilities
8.4 Control System
The control system employed for the purpose of this project is fairly simple. It consists of an Atmel
Atmega644P microcontroller, an L293D H-bridge circuit driver and the transmitting and receiving radios.
Any set of transmitting and receiving devices may be employed for this purpose; the possibility of
transmitting over a Bluetooth device was accessed and found to be plausible with not change to the
code required.
The atmega644P microcontroller is essentially the brain of the system. Its main function is to relay what
pins on the H-bridge circuit should be set high or low and in doing so dictates what motors are on and
what direction the current is flowing through each motor. The controller is also programmed to
communicate with the radio. In this specific application, the device has been programmed to get data
from the radio and executes case statements based on input data. Due to familiarity with the language,
the device was programmed in C++.
25
Given that the controller would be communicating with radios and such communication is based on
Serial Periphal Interface protocol it was necessary to write code specifically to facilitate this
communication. The code developed is shown in Appendix D under “nordic.c”. The control logic behind
the code is as follows; when the robot is powered on it begins walking forward and continues to do so
until the transmitting radio sends a different signal and the robot adjusts accordingly. This logic is
depicted in the flowchart as shown in Figure [8-5].
Figure 8-5 Control logic for CARL
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The L293D is a half H-bridge driver for DC electric motors. They can provide bi-directional control, and
isolate the motor power supply from the logic driver, the Atmega644P microprocessor. The schematic
for connecting the motor to the L293D and the L293D to the microcontroller is shown in Figure [8-6]. An
image of the board is shown in Figure [8-7] with the Atmega644p taken out to show the decoupling
capacitor that protects the microcontroller in the event that the motors draw too much current.
Figure 8-6 Atmega644p & L293D chips showing pin connections
27
Figure 8-7 Controller board
9 Modelling
RoboCAD decided to use SimMechanics to model and simulate the mechanical system that will be
incorporated into the design of CARL. The advantage of such simulation environments is that they
employ familiar block diagram-oriented modeling paradigms that simulate motion and analyze the
results without deriving the mathematical equations governing the system.
SimMechanics eliminates these by simulating the model’s rigid motion by integrating the multiple
bodies and joints whilst universally lumping the geometric constraints and multiple local coordinate
systems that are inherent to the motion of walking using a mechanized bipedal walker. RoboCAD’s
SimMechanics simulation has incorporated analysis of human leg locomotion as well as the forward
dynamic analysis of CARL’s legs taking into careful consideration force, torque, acceleration, velocity
and finally and most importantly the position of specific points on the legs.
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9.1 Developing References through capture of human leg locomotion
The reference trajectory for CARL is based on observing the kinetic motion of human locomotion.
Ultimately, this reference is the basis of the desired trajectory of slow controlled movement that CARL
will undergo. To accomplish this LED diode were attached to central areas located on the hip, knee and
ankle joints of the human leg when viewed from a side profile.
Each LED diode emits a different colour in order to eliminate confusion when analyzing the trajectories
of the LED diodes. Due to the difference in size of the reference model and CARL a scaling ratio was used
to approximate the respective dimensions of the robot. The length of the human leg measuring
approximately one metre and CARL’s legs measuring 13 inches, therefore the ratio is 1:3. Most
importantly, the trajectories shown below are relative to a fixed point on the earth whose simulation in
SimMechanics is detailed further on.
Human gait analysis was accomplished using an ordinary digital SLR camera (figure [9-1]) for image
capture and the movement analysis software was provided by the International Society of Biomechanics
for the 2-D kinematic analysis of movement and rigid body position analysis. Two dimensional analysis is
easier, faster and sometimes more accurate than three dimensional analysis. However, the most
dominant error that were encountered during the two dimensional analysis to motion with out-of-plane
components included system noise due to irregular movement of the inter-segmental joints of the leg
therefore producing noise on the plots of position. This occurs because when walking the human leg
adjusts itself marginally in real-time to ensure balance which is an anthropometric characteristic
inherent to human legs.
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Figure 9-1 SLR camera
In the study and research of human locomotion analysis most sources included measurable parameters
and their interpretation which included temporal and spatial analysis of speed, pitch, and dynamic
electromyography, which studies muscle activity during gait. These have not been covered in our scope
because CARL’s system was not designed to consider these aspects, which would incorporate springs
and dampers.
Figure 9-2 positions of the hip, knee, and ankle joints during walking
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These graphs, as shown in figure [9-2] show plots of position in the horizontal direction or sagittal plane
(X axis) and the vertical direction or caudal plane (Y axis). Note that the foot position in this figure
follows the foot position shown in figure [7-1].
9.2 Ground and Collision Simulation (Simulink)
According to the Physical Therapy Dictionary website, "ground reaction force" is simply defined as the
reaction to the force the body exerts on the ground. This force is measurable by incorporating
biomechanics and physics equations to allow an athlete or therapy patient feedback on the amount of
force he or she must apply to the ground in order to execute a particular movement. In SimMechanics,
the ground refers to a body of infinite mass that acts as a reference frame at rest for a whole
machine and as a fixed base for attaching machine components. Although this enables the
specification of the degrees of freedom of our system relative to its surroundings, RoboCAD has
sought to eliminate this analysis as it requires syndicated knowledge and analysis study that is
currently out of our scope. The machine environment incorporates a feature in which there is a
dynamic interaction between the feet and the ground during walking. The dynamic analysis,
kinematic analysis and control of CARL are important research areas that will be expanded in
more detail in the next report with real-time analysis of the built model. The elasticity in
conventionally built walking robots is an undesired effect that needs to be eliminated. This
complex phenomenon encompasses energy transmittal with the ground and this creates control
difficulty and this includes the influence of friction which will not be covered in our study and tests.
The linearization model of the ground is shown below and evaluates the model on a level
ground surface with a physically, realistic interaction model based on analyzing the vertical
ground reaction forces that are approximated by nonlinear spring-damper interaction. CARL’s body
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dynamics contribute to the stability, energy efficiency and responsive diversity of legged
locomotion that can be adjusted and improved by adjusting the speed of the motor that drives
the robot.
Figure 9-3 Current ground model accounting for position and velocity
10 Analysis
10.1 Foot Locus of Leg Linkages
To determine the motion of the foot relative to the rotating crank arm, executing a motion analysis of
the entire Theo Jansen Mechanism is necessary. The mechanism is shown below in figure [10-1].
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Figure 10-1 Theo Jansen Mechanism Linkages
The entire body of the robot is in translation along the y-axis as a result of the rotation of the crank arm,
“m”. To facilitate the motion analysis, any linkages that only move along the same path as the
translating body of the robot can be treated as stationary. Essentially, any movement in the y-axis can
be ignored so long as the magnitude of its velocity is the same as the overall velocity of the translating
body (Rideout, 2013).
Using this assumption, links “a” and “e” in Figure [10-1] can be treated as a stationary base and is crucial
in developing the kinematic equations. It is also assumed that the motor rotates the crank arm at a
constant angular velocity and as such the angular acceleration of the crank arm is zero. To determine
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the position of each link along with its angular velocities and accelerations as the crank arm rotates, only
three sets of equations are necessary and they are based on the three sets of vector loops.
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10.1.1 Vector Loops
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For equations (1) – (9), the lengths of each link are known. These lengths are denoted as “rn” and are
based on scaled versions of the dimensions specified by Theo Jansen, the mechanism`s designer. The
crank arm is treated as the input arm, and as such, its position, angular velocity and angular acceleration
have been predetermined. The equations are used to determine the angular positions of each link as the
crank arm rotates as well as their angular velocities and accelerations. The main intention of solving
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these equations is to determine the position of link 8 along with its angular velocity and acceleration as
this would determine the motion of foot relative to the rotation of the crank arm.
Equations (1) – (9) were rewritten and solved using Matlab to yield the locus of the foot seen in Figure
[10-2]. The rewritten equations are shown in Appendix A, “Motion Analysis”. The Matlab code used in
producing Figure [10-2] can be seen in Appendix B, “Motion Analysis Matlab Code”.
Figure 10-2 MATLAB foot position
10.1.2 Quality
Figure [10-2] shows the locus of the Theo Jansen mechanism generated using Matlab code. It provides
information about the stride of the robot based on the current design specifications. Using the above
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plot it is possible to determine the stride length and the step height of the leg linkage. The stride length
can be determined by calculating the difference between the minimum and maximum values of position
on the x-axis. Similarly, the step height can be determined by calculating the difference between the
maximum and minimum position values on the y-axis. The resulting values are shown in Table [10-1]
Stride Length (inches) 1.5
Step Height (inches) 5.5
Table 10-1
The information in the table above shows that the stride length is 1.5 inches which represents
approximately 12.5% of the robot’s overall height. The robot is 9.31 inches in width and as such, the
stride represents 16.1 % of this value. This meets the design requirements set in the design objectives
listed in the research and concept development report.
Table [10-1] also shows that the step height is 5.5 inches. This height should be significant enough to
traverse any irregularities on the terrain’s surface. As mentioned in the design objectives, this will
reduce the forces on the foot that cause tipping and improve the robot’s stability in its stride. The step
height is also sufficient enough to prevent the feet from dragging and minimize energy loss.
Figure [10-2] suggests that the placing event time is approximately the same duration of time as the
lifting event. This is because the plot shows that the both sets of events occur one above the other; the
upper half of the locus, the lifting event, and the lower half of the locus, the placing event, stretch over
the same space in the x-axis. This indicates a duty factor of approximately 0.5, this is in-line with the
design objectives set for this project.
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Given that both legs follow the exact same design specifications and are merely offset by a phase angle
of 180 degrees, it stands to reason the loci of both legs should be exactly the same barring minor
differences that could arise due to manufacturing tolerances.
10.2 Gait Selection
Given that the robot is essentially a two legged walker, gait selection is limited to equal cycle phase
gaits. Since only one motor will be driving the crank arm of both feet and there are only two feet, the
only possible gait that can be employed is a full cycle equal phase gait. The second leg is offset by 180
degrees. A gait diagram is shown below (figure [10-3]) to illustrate the motion of the robot as it walks
along in the direction shown.
Figure 10-3 Gait Diagram
10.3 Pin Forces
In order to determine the torque required to create the desired motion it becomes necessary to take
the information obtained from the acceleration analysis to generate and the mass properties of Plexiglas
to solve for the forces acting on each pin as well as the torque required at the crank arm. This exercise
should provide a minimum motor size requirement and by proxy provide an indication as to the battery
size required to power said motor.
At this stage in the project, the equations have been developed to solve for the forces and they can be
seen in Appendix B “Inverse Dynamics Hand Calculations”.
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11 Conclusions
Starting from a few concepts, with research into the available resources concerning humanoid robotics,
a prototype of CARL, our actively controlled biped robot has been created. Taken into consideration the
energy and costs of the project, various objectives were met; the machine is self-balancing, durable, and
is user friendly. This task was met through extensive research in the stability and walking motion of
humans and in robotics. The stability phase of the project consisted of the leg design based from Theo-
Jensens’ Strandbeest, which aims to mimic the foot locus of humans, and the weight distributions
provided by the shifting center of mass; from the unstable leg to the stable. To verify the validity of the
simulations, we’ve also taken the opportunity to perform analytical hand calculations of the position,
velocities, and accelerations of the major links and joints in the system.
We did not, however, in the end, manage to meet one major goal, which was to have the prototype
function. Due to a deficiency of time and resources, we were not able to install the gears necessary for
the coupling motion of the legs with the weight balancing mechanism provided by the scotch-yoke
concept outlined in this report. We did, however, construct the legs, foot, and the control system for the
machine.
Considerations for improvements are wide. One of the major issues encountered during the completion
of the term was the fact that during the research component of the project, many sources have lumped
the varying human components of the leg into large segmented polygons so simplify the movement of
their models. The issue, however, with this is the fact that the adaptability that humans have on various
terrain cannot be remodelled as a simple system of 2-3 polygons. As a suggestion, further time and
resources should be put into the prototype such that the robot legs mimic the human leg as much as
possible.
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Another consideration was the construction phase of the project. Due to the limitations of the tools
used to create the pieces of the robot, there were variations and alterations of the part dimensions. This
meant that a lot of time had gone to make reparations of these errors. Since the processes were done
by hand, instead of with the laser cutter and the rapid prototyping machine, the robot, CARL, was
susceptible to dimensional inconsistencies.
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12 Appendix A – Motion Analysis (Hand Calculations)
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13 Appendix B – Inverse Dynamics (Hand Calculations)
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14 Appendix C – Motion Analysis Code (MATLAB) close all
clear all
a = 3.80
b = 4.15
c = 3.93
d = 4.01
e = 5.58
f = 3.94
g = 3.67
h = 6.57
ilink = 4.90
j = 5.00
k = 6.19
l = 0.78
m = 1.50
r1 = sqrt((a^2 )+(e^2))
r2 = m
r3 = j
r4a = b
r4b = d
r5 = k
r6 = c
r7 = f
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r8a = g
%
n = 400;
t = linspace(0,10,n);
theta2dot = 1;
theta1 = pi;
%
% Position analysis
%
% Loop 1
for i=1:n
theta2(i) = theta2dot*t(i);
a(i) = 2*r2*r4a*cos(theta2(i)) - 2*r1*r4a*cos(theta1);
b(i) = 2*r2*r4a*sin(theta2(i)) - 2*r1*r4a*sin(theta1);
c(i) = (r1^2) + (r2^2) + (r4a^2) - (r3^2) -(2*r1*r2*((cos(theta1)*cos(theta2(i))) +
(sin(theta1)*sin(theta2(i)))));
theta4a(i) = 2*atan((-b(i)-sqrt(b(i)^2 - c(i)^2+a(i)^2))/(c(i)-a(i)));
theta4b(i) = theta4a(i) - ((90*pi)/180);
theta3(i) = acos(((r1*cos(theta1))-(r2*cos(theta2(i)))-(r4a*cos(theta4a(i))))/r3);
end;
% Loop 2
for i = 1:n
a2(i) = 2*r3*r6*cos(theta3(i)) + 2*r4a*r6*cos(theta4a(i));
b2(i) = 2*r3*r6*sin(theta3(i)) + 2*r4a*r6*sin(theta4a(i));
c2(i) = r3^2 + r6^2 + r4a^2 - r5^2 +
2*r3*r4a*((cos(theta3(i))*cos(theta4a(i))) +
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(sin(theta3(i))*sin(theta4a(i))));
theta6(i) = 2*atan((-b2(i)-sqrt(b2(i)^2 - c2(i)^2+a2(i)^2))/(c2(i)-a2(i)));
theta5(i) =
acos(((r3*cos(theta3(i)))+(r6*cos(theta6(i)))+(r4a*cos(theta4a(i))))/r5);
end;
% Loop 3
for i = 1:n
a3(i) = 2*r7*r6*cos(theta6(i)) - 2*r4b*r6*cos(theta4b(i));
b3(i) = 2*r7*r6*sin(theta6(i)) - 2*r4b*r6*sin(theta4b(i));
c3(i) = r7^2 + r6^2 + r4b^2 - r8a^2 +
2*r6*r4b*((cos(theta6(i))*cos(theta4b(i))) +
(sin(theta6(i))*sin(theta4b(i))));
theta7(i) = 2*atan((-b3(i)-sqrt(b3(i)^2 - c3(i)^2+a3(i)^2))/(c3(i)-a3(i)));
theta8a(i) = acos(((r7*cos(theta7(i)))+(r6*cos(theta6(i)))-(r4b*cos(theta4b(i))))/(-r8a));
end;
for i = 1:n
rGx(i) = (r2*cos(theta2(i))+ r5*cos(theta5(i))+
ilink*cos(theta8a(i)+(pi/2)));
rGy(i) = (r2*sin(theta2(i))+ r5*sin(theta5(i))+
ilink*sin(theta8a(i)+(pi/2)));
end;
for i = 1:n
%first loop
A = [-r3*sin(theta3(i)) (-r4a*sin(theta4a(i))); (r3*cos(theta3(i)))
r4a*cos(theta4a(i))];
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bv = [r2*theta2dot*sin(theta2(i)) ; -r2*theta2dot*cos(theta2(i))];
vel = inv(A)*bv;
th3dot(i) = vel(1);
th4dot(i) = vel(2);
%second loop
A = [-r5*sin(theta5(i)) r6*sin(theta6(i)); r5*cos(theta5(i)) -r6*cos(theta6(i))];
bv = [((-r4a*th4dot(i)*sin(theta4a(i)))-(r3*th3dot(i)*sin(theta3(i)))) ;
((r4a*th4dot(i)*cos(theta4a(i)))+(r3*th3dot(i)*cos(theta3(i))))];
vel2 = inv(A)*bv;
th5dot(i) = vel2(1);
th6dot(i) = vel2(2);
%
%third loop
A = [-r8a*sin(theta8a(i)) -r7*sin(theta7(i)); r8a*cos(theta8a(i)) -r7*cos(theta7(i))];
bv = [((-r4b*th4dot(i)*sin(theta4b(i)))-(r6*th6dot(i)*sin(theta6(i)))) ;
((r4b*th4dot(i)*cos(theta4b(i)))+(r6*th6dot(i)*cos(theta6(i))))];
vel3 = inv(A)*bv;
th8dot(i) = vel3(1);
th7dot(i) = vel3(2);
end;
%
for i = 1:n
%first loop
A = [ r3*sin(theta3(i)) (r4a*sin(theta4a(i)));(-r3*cos(theta3(i))) -r4a*cos(theta4a(i))];
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bv = [((-r4a*th4dot(i)^2*cos(theta4a(i))) - (r3*th3dot(i)^2*cos(theta3(i))) -
(r2*theta2dot^2*cos(theta2(i)))) ; ((-r4a*th4dot(i)^2*sin(theta4a(i))) -(r3*th3dot(i)^2*sin(theta3(i))) -
(r2*theta2dot^2*sin(theta2(i)))) ];
acl = inv(A)*bv;
th3dbldot(i) = acl(1);
th4dbldot(i) = acl(2);
%second loop
A = [-r5*sin(theta5(i)) r6*sin(theta6(i));r5*cos(theta5(i)) (-r6*cos(theta6(i)))];
bv = [((r5*th5dot(i)^2*cos(theta5(i)))- (r3*th3dot(i)^2*cos(theta3(i))) -(r4a*th4dot(i)^2*cos(theta4a(i)))-
(r6*th6dot(i)^2*cos(theta6(i))) -(r3*th3dbldot(i)*sin(theta3(i)))-(r4a*th4dbldot(i)*sin(theta4a(i)))) ;
((r5*th5dot(i)^2*sin(theta5(i)))- (r3*th3dot(i)^2*sin(theta3(i))) -(r4a*th4dot(i)^2*sin(theta4a(i)))-
(r6*th6dot(i)^2*sin(theta6(i))) +
(r3*th3dbldot(i)*cos(theta3(i)))+(r4a*th4dbldot(i)*cos(theta4a(i))))];
acl2 = inv(A)*bv;
th5dbldot(i) = acl2(1);
th6dbldot(i) = acl2(2);
%third loop
A = [-r8a*sin(theta8a(i)) r7*sin(theta6(i));r8a*cos(theta8a(i)) (-r7*cos(theta7(i)))];
bv = [((r8a*th8dot(i)^2*cos(theta8a(i)))- (r6*th6dot(i)^2*cos(theta6(i))) -
(r4b*th4dot(i)^2*cos(theta4b(i)))- (r7*th7dot(i)^2*cos(theta7(i))) -(r6*th6dbldot(i)*sin(theta6(i)))-
(r4b*th4dbldot(i)*sin(theta4b(i)))) ;
((r8a*th8dot(i)^2*sin(theta8a(i)))- (r6*th6dot(i)^2*sin(theta6(i))) -(r4b*th4dot(i)^2*sin(theta4b(i)))-
(r7*th7dot(i)^2*sin(theta7(i))) +
(r6*th6dbldot(i)*cos(theta6(i)))+(r4b*th4dbldot(i)*cos(theta4b(i))))];
acl3 = inv(A)*bv;
th8dbldot(i) = acl3(1);
th7dbldot(i) = acl3(2);
end;
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% Plots
%
figure(1)
plot(rGx,rGy);
ylabel('Step Height w.r.t Time');
xlabel('Horizontal Position');
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15 Appendix D – C++ code Walker.c #include <avr/io.h> #include<avr/sleep.h> #include<avr/interrupt.h> #include <avr/power.h> #include <avr/wdt.h> #include <util/delay.h> #include "nordic-nRF24L01.c" #define TRUE 1; #define FALSE 0; char old_index; int8_t running = FALSE; // define functions void init(void); void timer2_pwm_init(void); void handle_key(char key); char getkey(void); void timer2_pwm_init(void) {
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// set fast PWM, NON-INVERTING OUTPUT TCCR2A = _BV(COM2A1)|_BV(COM2B1)|_BV(WGM21)|_BV(WGM20); TCCR2B = 0; // timer stopped OCR2A = 0; OCR2B = 0; DDRD |= _BV(PD6)|_BV(PD7); // enable interrupts - for sleep TIMSK2 = _BV(TOIE2); //set 8-bit Timer/Counter2 Overflow Interrupt Enable // TIMSK2 = _BV(OCIE2A); // set interrupt mask to overflow TIFR2=0; //clear any pending timer interrupts } void init(void) { // disable watchdog timer MCUSR = 0; wdt_disable(); timer2_pwm_init(); init_nRF_pins();
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// set sleep mode to wait out interrupts set_sleep_mode(SLEEP_MODE_IDLE); } ISR(TIMER2_OVF_vect) // for ATMega644 { } char getkey() { char rxkey; uint8_t incoming, index; incoming = rx_send_byte(0xFF); // read status register if (incoming == 0xFF) return(0); // receiver not installed if (!(incoming & 0x40)) return(0); // no data received // otherwise we got data receive_data(); index = data_array[2]; // if (index == old_index) return(0); // old_index = index; rxkey = data_array[0] & 0x1F; // assumes low order 5 bits only used return(rxkey);
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} int main( void ) { char key; init(); PORTC = 0x00; // all off DDRC = 0x3F; // show byte in leds DDRD |= 0xFE; // port D has timer and control, usart output (PD0 is RxD0) PORTD = 0; // motor is in braking configure_receiver(); sei(); // enable interrupts PORTD |= _BV(PD2); PORTD &= ~(_BV(PD3) | _BV(PD4) | _BV(PD5)) // PORTD &= ~(_BV(PD2) | _BV(PD3) | _BV(PD4) | _BV(PD5)); OCR2A = 150; OCR2B = 150; // start timer // TCCR2B = _BV(CS22)|_BV(CS20); // update approx. 244 times per sec. at 8 MHz TCCR2B = _BV(CS21); // update approx. 488 times per sec. at 1 MHz // start control loop while ( 1 ) { key = getkey(); if (key) { PORTC = key; handle_key(key); } sleep_mode(); // sleep until timer interrupt // _delay_ms(5); } return 0; } void handle_key(char key) { switch (key) // center key { case 0x0F: // stop - center key PORTD &= ~(_BV(PD2) | _BV(PD3) | _BV(PD4) | _BV(PD5)); OCR2A = 0; OCR2B = 0; running = FALSE; break;
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case 0x1D: // forward or speed up - top key PORTD |= _BV(PD2); PORTD &= ~(_BV(PD3) | _BV(PD4) | _BV(PD5)); OCR2A = 100; OCR2B = 100; running = TRUE; break; case 0x1E: // backward or slow down - bottom key PORTD |= _BV(PD3); PORTD &= ~(_BV(PD2) | _BV(PD4) | _BV(PD5)); OCR2A = 100; OCR2B = 100; running = TRUE; break; case 0x17: // implement left turn - left button PORTD |= _BV(PD2)| _BV(PD4); PORTD &= ~(_BV(PD3) | _BV(PD5)); OCR2A = 100; OCR2B = 100; running = TRUE; break; case 0x1B: // implement right turn PORTD |= _BV(PD2)| _BV(PD5); PORTD &= ~(_BV(PD3) | _BV(PD4)); OCR2A = 100; OCR2B = 100; running = TRUE; break; default: break; } }
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Nordic. C // NRF24l01 transceiver code // adapted from original Sparkfun code // uses a 4 byte payload, to match the SF Nordic fob #define RX_PORT PORTB #define RX_PORT_PIN PINB #define RX_PORT_DD DDRB #define RX_CE 3 //Output #define RX_CSN 4 //Output #define RX_SCK 7 //Output #define RX_MOSI 5 //Output #define RX_MISO 6 //Input uint8_t data_array[4]; #define sbi(var, mask) ((var) |= (uint8_t)(1 << mask)) #define cbi(var, mask) ((var) &= (uint8_t)~(1 << mask)) uint8_t rx_address[5] = {0XE7, 0XE7, 0XE7, 0XE7, 0XE7}; // default uint8_t rx_channel = 2; // default //2.4G Configuration - Receiver
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void configure_receiver(void); //Sends one byte to nRF uint8_t rx_send_byte(uint8_t cmd); //Sends command to nRF uint8_t rx_send_command(uint8_t cmd, uint8_t data); //Set RX address - stored in eeprom void rx_send_rx_address(void); //Sends the 4 bytes of payload void rx_send_payload(uint8_t cmd); //Basic SPI to nRF uint8_t rx_spi_byte(uint8_t outgoing); void init_nRF_pins(void) { volatile char IOReg; //1 = Output, 0 = Input RX_PORT_DD |= (1<<RX_CE) | (1<<RX_MOSI) | (1<<RX_CSN) | (1<<RX_SCK); // Enable pull-up resistors RX_PORT = 0b11111110; // enable SPI in Master Mode with SCK = CK/4 // SPR1, SPR0 = 00 - divide by 4. 01 - by 16, 10 - by 64, 11 by 128 SPCR = (1<<SPE)|(1<<MSTR); // CK/4
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// SPCR = (1<<SPE)|(1<<MSTR)|(1<<SPR0); // CK/16 // SPCR = (1<<SPE)|(1<<MSTR)|(1<<SPR1); // CK/64 IOReg = SPSR; // clear SPIF bit in SPSR IOReg = SPDR; cbi(RX_PORT, RX_CE); //Stand by mode } //RX Functions //=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-= //Reads the current RX buffer into the data array //Forces an RX buffer flush void receive_data(void) { cbi(RX_PORT, RX_CSN); //Stand by mode rx_spi_byte(0x61); //Read RX Payload data_array[0] = rx_spi_byte(0xFF); data_array[1] = rx_spi_byte(0xFF); data_array[2] = rx_spi_byte(0xFF); data_array[3] = rx_spi_byte(0xFF); sbi(RX_PORT, RX_CSN); rx_send_byte(0xE2); //Flush RX FIFO
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rx_send_command(0x27, 0x40); //Clear RF FIFO interrupt sbi(RX_PORT, RX_CE); //Go back to receiving! } //2.4G Configuration - Receiver //This setups up a RF-24G for receiving at 1mbps void configure_receiver(void) { uint8_t channel; cbi(RX_PORT, RX_CE); //Go into standby mode rx_send_command(0x20, 0x39); //Enable RX IRQ, CRC Enabled, be a receiver rx_send_command(0x21, 0x00); //Disable auto-acknowledge rx_send_command(0x23, 0x03); //Set address width to 5bytes (default, not really needed) rx_send_command(0x26, 0x07); //Air data rate 1Mbit, 0dBm, Setup LNA rx_send_command(0x31, 0x04); //4 byte receive payload
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channel = rx_channel; if (channel < 84) // channels 84-127 are illegal { rx_send_command(0x25, channel); } else { rx_send_command(0x25, 0x02); //RF Channel 2 (default, not really needed) } rx_send_rx_address(); //Set RX address rx_send_command(0x20, 0x3B); //RX interrupt, power up, be a receiver sbi(RX_PORT, RX_CE); //Start receiving! } //Sends the 4 bytes of payload void rx_send_payload(uint8_t cmd) { uint8_t i; cbi(RX_PORT, RX_CSN); //Select chip rx_spi_byte(cmd);
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for(i = 0 ; i < 4 ; i++) rx_spi_byte(data_array[i]); sbi(RX_PORT, RX_CSN); //Deselect chip } void rx_send_rx_address() //Set RX address - stored in eeprom { uint8_t i,address; cbi(RX_PORT, RX_CSN); // Select chip rx_spi_byte(0x2A); // pipe 0 read address for(i = 0 ; i < 5 ; i++) { address = rx_address[i]; rx_spi_byte(address); } sbi(RX_PORT, RX_CSN); //Deselect chip } //Sends command to nRF
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uint8_t rx_send_command(uint8_t cmd, uint8_t data) { uint8_t status; cbi(RX_PORT, RX_CE); //Stand by mode cbi(RX_PORT, RX_CSN); //Select chip rx_spi_byte(cmd); status = rx_spi_byte(data); sbi(RX_PORT, RX_CSN); //Deselect chip return(status); } //Sends one byte to nRF uint8_t rx_send_byte(uint8_t cmd) { uint8_t status; cbi(RX_PORT, RX_CSN); //Select chip status = rx_spi_byte(cmd); sbi(RX_PORT, RX_CSN); //Deselect chip return(status);
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} //Basic hardware SPI uint8_t rx_spi_byte(uint8_t byte) { SPDR = byte; // send Character while (!(SPSR & (1<<SPIF))); // wait until Char is sent return (uint8_t) SPDR; }
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